Comparison of Distributed Beamforming Algorithms for MIMO Interference Networks
This paper presents a comparative study of algorithms for jointly optimizing beamformers and receive filters in an interference network, where each node may have multiple antennas, each user transmits at most one data stream, and interference is treated as noise. We focus on techniques that seek goo...
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| Vydané v: | IEEE transactions on signal processing Ročník 61; číslo 13; s. 3476 - 3489 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York, NY
IEEE
01.07.2013
Institute of Electrical and Electronics Engineers |
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| ISSN: | 1053-587X, 1941-0476 |
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| Abstract | This paper presents a comparative study of algorithms for jointly optimizing beamformers and receive filters in an interference network, where each node may have multiple antennas, each user transmits at most one data stream, and interference is treated as noise. We focus on techniques that seek good suboptimal solutions by means of iterative and distributed updates. Those include forward-backward iterative algorithms (max-signal-to-interference-plus-noise ratio (SINR) and interference leakage), weighted sum mean-squared error (MSE) algorithms, and interference pricing with incremental signal-to-noise ratio (SNR) adjustments. We compare their properties in terms of convergence and information exchange requirements, and then numerically evaluate their sum rate performance averaged over random (stationary) channel realizations. The numerical results show that the max-SINR algorithm achieves the maximum degrees of freedom (i.e., supports the maximum number of users with near-zero interference) and exhibits better convergence behavior at high SNRs than the weighted sum MSE algorithms. However, it assumes fixed power per user and achieves only a single point in the rate region whereas the weighted sum MSE criterion gives different points. In contrast, the incremental SNR algorithm adjusts the beam powers and deactivates users when interference alignment is infeasible. Furthermore, that algorithm can provide a slight increase in sum rate, relative to max-SINR, at the cost of additional iterations. |
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| AbstractList | This paper presents a comparative study of algorithms for jointly optimizing beamformers and receive filters in an interference network, where each node may have multiple antennas, each user transmits at most one data stream, and interference is treated as noise. We focus on techniques that seek good suboptimal solutions by means of iterative and distributed updates. Those include forward-backward iterative algorithms (max-signal-to-interference-plus-noise ratio (SINR) and interference leakage), weighted sum mean-squared error (MSE) algorithms, and interference pricing with incremental signal-to-noise ratio (SNR) adjustments. We compare their properties in terms of convergence and information exchange requirements, and then numerically evaluate their sum rate performance averaged over random (stationary) channel realizations. The numerical results show that the max-SINR algorithm achieves the maximum degrees of freedom (i.e., supports the maximum number of users with near-zero interference) and exhibits better convergence behavior at high SNRs than the weighted sum MSE algorithms. However, it assumes fixed power per user and achieves only a single point in the rate region whereas the weighted sum MSE criterion gives different points. In contrast, the incremental SNR algorithm adjusts the beam powers and deactivates users when interference alignment is infeasible. Furthermore, that algorithm can provide a slight increase in sum rate, relative to max-SINR, at the cost of additional iterations. |
| Author | Honig, Michael L. Utschick, Wolfgang Shi, Changxin Schmidt, David A. Berry, Randall A. |
| Author_xml | – sequence: 1 givenname: David A. surname: Schmidt fullname: Schmidt, David A. email: dschmidt@tum.de organization: Associate Institute for Signal Processing, Technische Universität München, Munich, Germany – sequence: 2 givenname: Changxin surname: Shi fullname: Shi, Changxin email: cshi@u.northwestern.edu organization: Department of Electrical Engineering and Computer Science, Northwestern University , Evanstion , US – sequence: 3 givenname: Randall A. surname: Berry fullname: Berry, Randall A. email: rberry@eecs.northwestern.edu organization: Department of Electrical Engineering and Computer Science, Northwestern University , Evanstion , US – sequence: 4 givenname: Michael L. surname: Honig fullname: Honig, Michael L. email: mh@eecs.northwestern.edu organization: Department of Electrical Engineering and Computer Science, Northwestern University, Evanstion , US – sequence: 5 givenname: Wolfgang surname: Utschick fullname: Utschick, Wolfgang email: utschick@tum.de organization: Associate Institute for Signal Processing, Technische Universität München, Munich, Germany |
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| Keywords | Performance evaluation MIMO system precoder optimization Coding circuit Updating Iterative method MIMO interference channel Beam forming Nodes Optimization Mean square error sum-rate maximization interference alignment Distributed algorithm Pricing Signal processing Numerical simulation Tariffication Signal to interference plus noise ratio beamforming Antenna array Information exchange Comparative study Signal to noise ratio |
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| SubjectTerms | Applied sciences Array signal processing beamforming Classification algorithms Convergence Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory Interference interference alignment Iterative methods MIMO interference channel Power control precoder optimization Pricing Resource management Signal and communications theory Signal processing algorithms Signal to noise ratio Signal, noise sum-rate maximization Telecommunications and information theory |
| Title | Comparison of Distributed Beamforming Algorithms for MIMO Interference Networks |
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